Why AI in Healthcare Hinges On A Solid Data Strategy

Artificial intelligence is only as effective as the data behind it. Without data that’s findable, accessible, interoperable and reusable — known as FAIR data — healthcare organizations risk inefficiencies, inaccuracies and unreliable AI-generated insights.

To unlock AI’s full potential, a well-structured data strategy built on FAIR principles must come first. According to Aashima Gupta, global director of healthcare solutions at Google Cloud, AI alone can’t solve all data challenges; success hinges on a strong data foundation.

“There’s a lot of AI hype, [and] there’s a lot of AI washing,” she said. “All the data projects have become AI projects, AI projects have become gen AI projects and gen AI has become agentic AI projects. But going back to enterprise has diverse starting points: Data matters, data strategy matters, and I would say there’s no gen AI or agentic AI strategy if you don’t have the data strategy.”

Gupta and Ted Slater, managing principal of scientific informatics knowledge engineering at EPAM Systems Inc., spoke with theCUBE’s Rebecca Knight at theCUBE’s Coverage of Google Cloud at HIMSS25, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the role of FAIR data in AI adoption.

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